Taking an AI MVP to Production

AI Development
Production Engineering
API Security
OpenAI SDK

Got an AI prototype built with Cursor, Bolt, Lovable, or a quick in-house build, and need it production-ready? I audit what's there, then harden the security, cost control, and reliability it needs for real users.

Taking an AI MVP to Production

If you've got a working AI prototype, built with Cursor, Bolt, Lovable, v0, or a quick in-house build, and it's time to put it in front of real users, this is that gap. AI prototypes are usually built for speed, not survival: no rate limiting, no fallback when the API times out, API keys sitting in code that ships to the browser. None of that shows up in a demo. All of it shows up in week one with real traffic.

AI Production Engineering

What's Included

  • Security review: exposed keys, auth gaps, and prompt injection risk
  • Cost control: rate limiting, caching, and usage monitoring for LLM API calls
  • Reliability: proper error handling and fallbacks for when the AI API fails or times out
  • Scaling: moving off prototype-grade infrastructure to something that holds up under real traffic
  • Test coverage for the parts of the system that actually need it before launch

My Approach

  1. Audit. A genuine read of what's there: what's solid, what's fragile, and what would actually break under real usage.
  2. Prioritise. Not every gap needs fixing before launch. I'll scope against what your actual launch date and user volume need, not a generic production checklist.
  3. Harden. Security, cost control and reliability work, built on Laravel and the OpenAI SDK where the backend needs rebuilding, or directly on what's already there where it doesn't.
  4. Support after launch. Usage patterns from real users are where the next round of issues actually shows up, so ongoing monitoring and support matters more here than on a typical build.

This sits alongside my broader AI development services: that page is about building AI features from scratch, this one's specifically for taking something that already exists and making it safe to launch.

Let's Talk About Your Prototype

Got an AI MVP that's ready for real users, or close to it? Get in touch and I'll give you an honest read on what it actually needs before launch.

Frequently asked questions

My AI MVP works fine in testing. What actually breaks in production?

Usually the same handful of things: API keys exposed in client-side code, no rate limiting so one user's usage can spike your OpenAI bill overnight, no fallback when the AI API times out or errors, and no caching so identical requests get billed repeatedly. None of these show up in a demo. All of them show up within the first week of real users.

Do you need to rebuild the whole thing, or can you work with what's there?

The audit tells me, not a default answer. A lot of AI prototypes have the right idea and a genuinely usable UI, with the actual gaps confined to the backend: auth, error handling, and how the AI API is called. That's usually a hardening job, not a rebuild. If the architecture itself won't hold up, I'll say so honestly rather than patch around it.

How do you get LLM API costs under control?

Rate limiting per user, caching repeated or similar requests, setting sensible token limits, and actual usage monitoring so a cost spike is visible before the bill arrives, not after. Most runaway AI costs come from a prototype that was never designed to say no to a request.

I built this with an AI coding tool and I'm not really a developer. Can you still help?

Yes, this is common. I'll read what's there, tell you honestly what state it's in, and take it from there without judging how it got built. The starting point doesn't matter much; what matters is whether it's safe to put in front of real users.

What does 'production-ready' actually include?

Proper authentication, rate limiting, error handling for when the AI API fails or times out, cost monitoring, basic test coverage, and a real deployment setup instead of whatever's currently running it. Not every project needs all of it on day one, so I'll scope against what your actual launch needs, not a generic checklist.

Let's chat about your next project

Whether you need a single contractor or a full team, I run every project through Storm Digital, the studio I co-founded. Having delivered large-scale projects for businesses of every size, I bring that same commitment to clients locally in Surrey, London, and worldwide.

See also...

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Stock Investment App

Real-time stock investment app for web and mobile, built with TypeScript, React, and WebSockets, delivering fast, responsive, and data-driven experiences.

KickTown Football - Website

Custom-built website and API's for KickTown Football, integrating a merchandise store, booking system, and seamless user experience.

Tempest Rising - Official Website

Website development for Slipgate Ironworks' Tempest Rising, crafted to deliver a sleek, immersive experience for fans and players.

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Oriental Garden Restaurant - Website Redesign

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Brands I've had the privilege to contribute to...

Logo for Slipgate Studios
Logo for Evolve
Logo for Disney
Logo for Heathrow
Logo for BAE Systems
Logo for University of Surrey
Logo for Allergan
Logo for OKA
Logo for Ribena
Logo for NARS